Students in the Master's programs in Statistics:
Questions about specific course work should be directed to the
advising team (email address: stat-ms-ad@umich.edu) or to your assigned faculty advisor.
Please go to this page to this page
set up an appointment
with me or other advisors. Students in the dual Master's program are
welcome to sign up for an appointment with me.

Office hours in Fall 2018: 9--11am, Wednesday, WH 461

Prospective PhD students: Thank you for your interest. Admissions decision is
made a graduate admissions committee, please see
this link for further information. My apology if I am unable to respond to your enquiry
due to the large volume of such emails.

Synopsis: Statistical inference is the computational process of turning data into statistics, prediction
and understanding. I work with richly structured data, such as those
extracted from texts, images and other
spatiotemporal signals.

In recent years I have gravitated toward a
field in statistics known as Bayesian nonparametrics, which provides
a fertile and powerful mathematical framework for the development of
many computational and statistical modeling ideas. The spirit of
Bayesian nonparametric statistics is to enable the kind of
inferential procedures according to which both the statistical modeling
and computational complexity may adapt to increasingly large and
complex data patterns in a graceful and effective way.
In this framework, stochastic processes and random measures, along with
latent variable models such as mixture, hierarchical and graphical
models figure prominently. My group's research is centered around
the interaction
between statistical inference and the theory of optimal transport
that arises in the learning of complex hierarchical models.

My motivation for all this came originally from an interest in
machine learning, which continues to be a major source of active
research interest.
A primary focus in our machine learning research is to develop more effective
inference algorithms using variational, stochastic and geometric viewpoints.

Fun statistics: number of papers I have written that has a giant's name
in the title, as of twenty eighteen: Bayes = 6; Dirichlet = 4; Gauss = 2; Wasserstein = 1; Lyapunov = 1;
Names I wish to appear on my paper's title: Blackwell, De Finetti, Riemann, Stein,